Võrdle meetodeid

	Simulatsioonipõhine kinnitav uurimus	Monte Carlo simulatsioon
Valdkond	Uurimisdisain	Otsustamine
Perekond	Process / pipeline	MCDM
Tekkeaasta	1980s–2000s (widespread integration in behavioral and social sciences)	1949
Looja	No single originator; tradition formalized through Monte Carlo methods (Metropolis & Ulam, 1949) applied to confirmatory designs	Metropolis, N., Ulam, S.
Tüüp	Quantitative hybrid design	Robustness wrapper — Monte Carlo uncertainty propagation
Algallikas	Morey, R. D., Chambers, C. D., Aitken, M. R. F., Harris, C. R., Hoekstra, R., Lakens, D., Lewandowsky, S., Morey, C. C., Newman, D. P., Schonbrodt, F. D., Vanpaemel, W., Wagenmakers, E. J., & Zwaan, R. A. (2022). The Peer Reviewers' Openness Initiative: Incentivising open research practices through peer review. Royal Society Open Science, 3(1), 150547.	Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association
Rööpnimetused	simulation-based confirmatory design, Monte Carlo confirmatory research, computational confirmatory study, simulation-enhanced hypothesis testing	—
Seotud	5	0
Kokkuvõte	Simulation-assisted confirmatory research integrates computational simulation — most commonly Monte Carlo methods — into a hypothesis-driven, confirmatory study design. Before or alongside empirical data collection, the researcher runs simulated data under specified model assumptions to establish expected parameter distributions, verify statistical power, and anticipate the behavior of the chosen analysis. The empirical findings are then evaluated against those simulation-derived benchmarks, strengthening the evidential value of confirmatory conclusions.	MONTE-CARLO-SIMULATION (Monte Carlo Simulation — Stochastic uncertainty propagation through MCDM model) is a ranking multi-criteria decision-making (MCDM) method introduced by Metropolis, N., Ulam, S. in 1949. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.